To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org

1. GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
Constructing Load-Balanced Data Aggregation Trees in
Probabilistic Wireless Sensor Networks
Abstract
Data Gathering is a fundamental task in Wireless Sensor Networks (WSNs). Data gathering
trees capable of performing aggregation operations are also referred to as Data
Aggregation Trees (DATs). Currently, most of the existing works focus on constructing
DATs according to different user requirements under the Deterministic Network Model
(DNM). However, due to the existence of many probabilistic lossy links in WSNs, it is more
practical to obtain a DAT under the realistic Probabilistic Network Model (PNM). Moreover,
the load-balance factor is neglected when constructing DATs in current literatures.
Therefore, in this paper, we focus on constructing a Load-Balanced Data Aggregation Tree
(LBDAT) under the PNM. More specifically, three problems are investigated, namely, the
Load-Balanced Maximal Independent Set (LBMIS) problem, the Connected Maximal
Independent Set (CMIS) problem, and the LBDAT construction problem. LBMIS and CMIS
are well-known NP-hard problems and LBDAT is an NP-complete problem. Consequently,
approximation algorithms and comprehensive theoretical analysis of the approximation
factors are presented in the paper. Finally, our simulation results show that the proposed
algorithms outperform the existing state-of-the-art approaches significantly.
Existing system
Data Gathering is a fundamental task in Wireless Sensor Networks (WSNs). Data gathering
trees capable of performing aggregation operations are also referred to as Data
Aggregation Trees (DATs). Currently, most of the existing works focus on constructing

2. DATs according to different user requirements under the Deterministic Network Model
(DNM). However, due to the existence of many probabilistic lossy links in WSNs, it is more
practical to obtain a DAT under the realistic Probabilistic Network Model (PNM). Moreover,
the load-balance factor is neglected when constructing DATs in current literatures.
Proposed system
we focus on constructing a Load-Balanced Data Aggregation Tree (LBDAT) under the PNM.
More specifically, three problems are investigated, namely, the Load-Balanced Maximal
Independent Set (LBMIS) problem, the Connected Maximal Independent Set (CMIS)
problem, and the LBDAT construction problem. LBMIS and CMIS are well-known NP-hard
problems and LBDAT is an NP-complete problem. Consequently, approximation algorithms
and comprehensive theoretical analysis of the approximation factors are presented in the
paper. Finally, our simulation results show that the proposed algorithms outperform the
existing state-of-the-art approaches significantly.
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
 Processor - Pentium –IV
 Speed - 1.1 Ghz
 RAM - 256 MB(min)
 Hard Disk - 20 GB

3. SOFTWARE CONFIGURATION:-
 Operating System : Windows XP
 Programming Language : JAVA
 Java Version : JDK 1.6 & above.